Abstract: The fully coupled WRF/Chem (Weather Research and Forecasting/Chemistry) model is used to simulate air quality over coastal areas of the Sea of Japan. The anthropogenic surface emissions database used as input for this model was based primarily on global hourly emissions data (dust, sea salt, and biomass burning), RETRO (REanalysis of the TROpospheric chemical composition), GEIA (Global Emissions Inventory Activity), and POET (Precursors of Ozone and their Effects in the Troposphere). Climatologic concentrations of particulate matter derived from the Regional Acid Deposition Model (RADM2), chemical mechanism, and the Secondary Organic Aerosol Model (MADE/SORGAM) with aqueous reactions were used to deduce the corresponding aerosol fluxes for input to the WRF/Chem model. The model was first integrated continuously over 48 hours, starting from 00:00 UTC on 14 March 2008, to evaluate ozone concentrations and other precursor pollutants. WPS meteorological data were used for the WRF/Chem model simulation in this study. Despite the low resolution of global emissions and the weak density of the local point emissions, it was found that the WRF/Chem model simulates the diurnal variation of the chemical species concentrations over the coastal areas of the Sea of Japan quite well. The Air Quality Management Division of the Ministry of the Environment in Japan selected the maximum level of the air quality standard for ozone, which is 60 ppb. In this study, the atmospheric concentrations of ozone over the coastal area of the Sea of Japan were calculated to be 30–55 ppb during the simulation period, which was lower than the Japanese air quality standard for ozone.

Abstract: The Arctic atmospheric boundary layer (AABL) in the central Arctic was characterized by dropsonde, lidar, ice thickness and airborne in situ measurements during the international Polar Airborne Measurements and Arctic Regional Climate Model Simulation Project (PAMARCMiP) in April 2009. We discuss AABL observations in the lowermost 500 m above (A) open water, (B) sea ice with many open/refrozen leads (C) sea ice with few leads, and (D) closed sea ice with a front modifying the AABL. Above water, the AABL had near-neutral stratification and contained a high water vapor concentration. Above sea ice, a low AABL top, low near-surface temperatures, strong surface-based temperature inversions and an increase of moisture with altitude were observed. AABL properties and particle concentrations were modified by a frontal system, allowing vertical mixing with the free atmosphere. Above areas with many leads, the potential temperature decreased with height in the lowest 50 m and was nearly constant above, up to an altitude of 100–200 m, indicating vertical mixing. The increase of the backscatter coefficient towards the surface was high. Above sea ice with few refrozen leads, the stably stratified boundary layer extended up to 200–300 m altitude. It was characterized by low specific humidity and a smaller increase of the backscatter coefficient towards the surface.

Abstract: Smoke plume rise is critically dependent on plume updraft structure. Smoke plumes from landscape burns (forest and agricultural burns) are typically structured into “sub-plumes” or multiple-core updrafts with the number of updraft cores depending on characteristics of the landscape, fire, fuels, and weather. The number of updraft cores determines the efficiency of vertical transport of heat and particulate matter and therefore plume rise. Daysmoke, an empirical-stochastic plume rise model designed for simulating wildland fire plumes, requires updraft core number as an input. In this study, updraft core number was gained via a cellular automata fire model applied to an aerial ignition prescribed burn conducted at Eglin AFB on 6 February 2011. Typically four updraft cores were simulated in agreement with a photo-image of the plume showing three/four distinct sub-plumes. Other Daysmoke input variables were calculated including maximum initial updraft core diameter, updraft core vertical velocity, and relative emissions production. Daysmoke simulated a vertical tower that mushroomed 1,000 m above the mixing height. Plume rise was validated by ceilometer. Simulations with two temperature profiles found 89–93 percent of the PM2.5 released during the flaming phase was transported into the free atmosphere above the mixing layer. The minimal ground-level smoke concentrations were verified by a small network of particulate samplers. Implications of these results for inclusion of wildland fire smoke in air quality models are discussed.

Abstract: The present study has used Meteosat infrared brightness temperature images to investigate the regional and interannual variability of Central African cloudiness. Spatial and temporal variability were investigated using half–hourly data from the Meteosat-7 during June–July–August (JJA) of 1998–2002. The full domain of study (1.5E–17E, 1N–15N) was divided into six regions and statistics in each region were derived. Analysis of the dependence of cloud fraction to the brightness temperature threshold is explored both over land and ocean. Three diurnal cycle regimes (continental, oceanic, and coastal) are depicted according to the amplitude and peak time. Over regions of relatively flat terrain, results indicate enhancement of deep convection in the afternoon followed by a gradual decrease in the night. The diurnal cycle of convection is characterised by afternoon and early evening (around 15:00–18:00 LST) maxima located mainly downwind of the major mountain chains, and a more rapid nighttime decay. In terms of the harmonic amplitude, the diurnal signal shows significant regional contrast with the strongest manifestation over the Adamaoua Plateau and the weakest near the South Cameroon Plateau. This remarkable spatial dependence is clear evidence of orographic and heterogeneous land-surface impacts on convective development. Oceanic region exhibits weak activity of convective cloudiness with a maximum at noon. It is suggested that daytime heating of the land surface and moist environment may play a role in determining the spatial distribution of cloud fraction. This study further demonstrates the importance of the Cameroon coastline concavity and coastal mountains in regulating regional frequencies of convection and their initialization. The strength of the diurnal cycle of convective activity depends on mountain height, mean flow, coastal geometry.

Abstract: Air quality models are increasingly used to develop estimates of dry and wet deposition of sulfate and nitrate in watersheds (because of lack of measurements) in an effort to determine the acidifying deposition load into the aquatic systems. These models need to be rigorously evaluated to ensure that one can rely on the modeled quantities instead of the measured quantities. In the United State (U.S.), these models have been proposed for use in establishing national standards based on modeled quantities. The U.S. Environmental Protection Agency (EPA) is considering aquatic acidification as the main ecological endpoint of concern in determining the secondary national ambient air quality standards for nitrogen oxides and sulfur oxides. Acidification is tied to depositions of sulfur and nitrogen, which are linked to ambient concentrations of the elements. As EPA proposes to use a chemical transport model in linking deposition to ambient concentration, it is important to investigate how the currently used chemical transport models perform in predicting depositions and ambient concentrations of relevant chemical species and quantify the variability in their estimates. In this study, several annual simulations by multiple chemical transport models for the entire continental U.S. domain are evaluated against available measurement data for depositions and ambient concentrations of sulfur oxides and reactive nitrogen species. The model performance results vary by evaluation time-scale and geographical region. Evaluation of annualized quantities (annual average ambient concentrations and annual total depositions) suppresses the large variances shown in the evaluation using the observation’s native shorter-term time-scales (e.g., weekly). In addition, there is a large degree of bias and error (especially for deposition fluxes) in the modeling results that brings to question the suitability of using air quality models to provide estimates of deposition loads. Variability in the ratio of deposition to ambient concentration, so-called the Transference Ratio that EPA has proposed to use in linking deposition to ambient concentration, is also examined. Our study shows that the Transference Ratios as well as total reduced nitrogen deposition, another modeled parameter EPA proposed to use in the process of determining the new secondary standard, vary considerably by geographical region and by model simulation.

Abstract: Based on the atmospheric regional climate model HIRHAM5, the single-column model version HIRHAM5-SCM was developed and applied to investigate the performance of a relative humidity based (RH-Scheme) and a prognostic statistical cloud scheme (PS-Scheme) in the central Arctic. The surface pressure as well as dynamical tendencies of temperature, specific humidity, and horizontal wind were prescribed from the ERA-Interim data set to enable the simulation of a realistic annual cycle. Both modeled temperature and relative humidity profiles were validated against radio soundings carried out on the 35th North Pole drifting station (NP-35). Simulated total cloud cover was evaluated with NP-35 and satellite-based ISCCP-D2 and MODIS observations. The more sophisticated PS-Scheme was found to perform more realistically and matched the observations better. Nevertheless, the model systematically overestimated the monthly averaged total cloud cover. Sensitivity studies were conducted to assess the effect of modified “tuning” parameters on cloud-related model variables. Two tunable parameters of the PS-Scheme and six tuning parameters contained in the cloud microphysics were analyzed. Lower values of the PS-Scheme adjustment parameter q0, which defines the shape of the symmetric beta distribution (acting as probability density function), as well as higher values of the cloud water threshold CWmin or autoconversion rate γ1 are able to reduce the overestimation of Arctic clouds. Furthermore, a lower cloud ice threshold γthr, which controls the Bergeron–Findeisen process, improves model cloudiness and the ratio of liquid to solid water content.